The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples
Abstract
Serum proteins may often serve as indicators of disease and is a rich source for biomarker discovery. However, the large dynamic range of proteins in serum makes the analysis very challenging because high‐abundant proteins tend to mask those of lower abundance. A prefractionation step, such as depletion of a few high‐abundant proteins before protein profiling, can assist in the discovery and detection of less abundant proteins that may prove to be informative biomarkers. In the present study, five different depletion columns were investigated considering efficiency, specificity, and reproducibility. Our research included quantitative determination of total protein, albumin, and immunoglobulin G (IgG) concentrations, one‐ and two‐dimensional gels and mass spectrometric analysis of the serum samples before and after the depletion step. Our results showed that all five depletion columns tested removed albumin and IgG with high efficiency. We found that based on reproducibility and binding specificity, the Multiple Affinity Removal Column that removed a total of six high‐abundant proteins (albumin, IgG, antitrypsin, IgA, transferring, and haptoglobin) offered the most promising depletion approach. Among the disposable (single‐use) products, the ProteoExtract™ Albumin/IgG Removal kit displayed the best results. Depleted serum from the Multiple Affinity Removal column was further evaluated by 2‐D gel electrophoresis (2‐DE) analysis, and the results indicated increased resolution and improved intensity of low‐abundant proteins in a reproducible fashion. Our study provides a comprehensive investigation of commercially available depletion columns and will be of high importance for future proteomic studies on serum samples.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Anderson, N. L., & Anderson, N. G. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r200007-mcp200 · Cited by 4,414
Use of proteomic patterns in serum to identify ovarian cancer
Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07746-2 · Cited by 3,236
Cited by
Exosomes in bodily fluids are a highly stable resource of disease biomarkers
Boukouris, S., & Mathivanan, S. (2015) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201400114 · Cited by 586
Comparative Human Salivary and Plasma Proteomes
Loo, J. A., Yan, W., Ramachandran, P., & Wong, D. T. (2010) · Journal of Dental Research · doi:10.1177/0022034510380414 · Cited by 444
Depletion of Abundant Plasma Proteins and Limitations of Plasma Proteomics
Tu, C., Rudnick, P. A., Martinez, M. Y., Cheek, K. L., Stein, S. E., Slebos, R. J. C., & Liebler, D. C. (2010) · Journal of Proteome Research · doi:10.1021/pr100646w · Cited by 390
Adipokines: A treasure trove for the discovery of biomarkers for metabolic disorders
Lehr, S., Hartwig, S., & Sell, H. (2012) · PROTEOMICS – Clinical Applications · doi:10.1002/prca.201100052 · Cited by 352
Metadata
- Authors
- Björhall, K., Miliotis, T., & Davidsson, P.
- Venue
- PROTEOMICS
- Publisher
- Wiley
- Published
- 2005-01
- Volume
- 5
- Issue
- 1
- Pages
- 307-317
- ISSN
- 1615-9853 (ISSN-L)
- 1615-9861
- OpenAlex
- W1980788421
- Cited by
- 384
- References
- 2
- FWCI
- 18.51
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples. https://app.cochat.ai/papers/10.1002/pmic.200400900
- The paper
- Björhall, K., Miliotis, T., & Davidsson, P. (2005). Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples. PROTEOMICS. https://doi.org/10.1002/pmic.200400900
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.